scholarly journals Experimental Investigation and Optimization of Machining Parameters in Turning of Aluminum Alloy 075-T651

2021 ◽  
Vol 27 (4) ◽  
pp. 296-305
Author(s):  
Arpit Srivastava ◽  
Mukesh Kumar Verma ◽  
Ramendra Singh Niranjan ◽  
Abhishek Chandra ◽  
Praveen Bhai Patel
Keyword(s):  
Aluminum Alloy ◽  
Process Parameters ◽  
Cutting Speed ◽  
Radial Force ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Optimization Of Process Parameters ◽  
Feed Force ◽  
Aluminum 7075 ◽  
Aluminum Alloy 7075

Abstract Aluminum alloy 7075-T651 is a widely used material in the aviation, marine, and automobile sectors. The wide application marks the importance of this material’s research in the manufacturing field. This research focuses on optimizing input process parameters of the turning process in the machining of Aluminum 7075-T651 with a tungsten carbide insert. The input machining parameters are cutting speed, feed, and depth of cut for the output response parameters cutting force, feed force, radial force, material removal, and surface roughness of the workpiece. For optimization of process parameters, the Taguchi method, with standard L9 orthogonal array, is used. ANOVA is applied to obtain signifi-cant factors and optimal combinations of process parameters.

Micro Textured Cutting Inserts with Solid Lubrication as Alternative Coolant to Mineral Oil-Based Cutting Fluid in Turning Operation

2021 ◽  
Vol 13 (4) ◽  
Author(s):  
C. Divya ◽  
L. Suvarna Raju ◽  
B. Singaravel
Keyword(s):  
Process Parameters ◽  
Orthogonal Array ◽  
Inconel 718 ◽  
Cutting Speed ◽  
Solid Lubricants ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Turning Process ◽  
Optimization Of Process Parameters ◽  
Cutting Inserts

Turning process is a primary process in engineering industries and optimization of process parameters enhance the machining performance. Inconel 718 is a nickel-based superalloy, widely found applications in the manufacturing of blades, sheets and discs in aircraft engines and rocket engines. It provides toughness at low temperature, with stand high mechanical stresses at elevated temperature and creep resistance. In this work, turning process is carried out on Inconel 718 with micro whole textured cutting inserts filled with solid lubricants. Three different solid lubricants are used namely molybdenum-di-sulfide (MoS2), tungsten-di-sulfide (WS2) and calcium-di-fluoride (CaF2). Experiments are performed as per L9 orthogonal array. Statistical approaches such as orthogonal array, Signal-to-Noise (S/N) ratio and Analysis of Variance (ANOVA) are used to find the importance and effects of machining parameters. In this study, input parameters included are feed, cutting speed and depth of cut and output parameter includes surface roughness. Optimization of process parameters is carried out and the significance is estimated. The result suggested that WS2 followed by MoS2 and CaF2 given good surface finish value. Also, solid lubricant in machining enhances the sustainability in manufacturing.

scholarly journals Analysis of Surface Roughness and Cutting Forces in Hard Turning of 42CrMo4 Steel using Taguchi and RSM Method

Mechanika ◽  
2020 ◽  
Vol 26 (3) ◽  
pp. 231-241 ◽  
Author(s):  
Mustafa ÖZDEMİR ◽  
Mehmet Tuncay KAYA ◽  
Hamza Kemal AKYILDIZ
Keyword(s):  
Surface Roughness ◽  
Feed Rate ◽  
Cutting Forces ◽  
Tangential Force ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Radial Force ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Feed Force

In this study, effects of cutting speed (V), feed rate (f), depth of cut (a) and tool tip radius (R) on  surface roughness (Ra, Rz, and Rt) and cutting forces (radial force (Fx), tangential force (Fy), and feed force (Fz)) in hard finish turning processes of hardened 42CrMo4 (52 HRC) material was investigated experimentally. Taguchi’s mixed level parameter design (L18) is used for the experimental design (2x1,3x3). The signal-to-noise ratio (S/N) was used in the evaluation of test results.  By using Taguchi method, cutting parameters giving optimum surface roughness and cutting forces were determined. Regression analyses are applied to predict surface roughness and cutting forces. Analysis of variance (ANOVA) is used to determine the effects of the machining parameters on surface roughness and cutting forces. According to ANOVA analysis, the most important cutting parameters were found to be feed rate for surface roughness and depth of cut among cutting forces.  By conducting validation experiments, optimization was seen to be applied successfully.

scholarly journals Effectiveness of Near-Dry Machining on Tool Performance in Bull Nose Milling of Aluminum Alloy 7075-T6

2019 ◽  
Vol 9 (2) ◽  
pp. 4751-4755
Keyword(s):  
Aluminum Alloy ◽  
Tool Wear ◽  
Flow Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Time Interval ◽  
Machining Parameters ◽  
Dry Machining ◽  
Aluminum Alloy 7075 ◽  
Five Axes

The paper investigated the effectiveness of near-dry machining also known as minimum quantity lubrication (MQL) on tool wear when aluminum alloy 7075-T6 was milled using bull nose carbide insert. The foregoing study found that the high tool wear was occurred in machining aluminum alloy 7075-T6 with uncoated carbide under dry machining. Due to that, dry machining was performed to examine its result with MQL. Different values of cutting parameter selected were cutting speed of 500 and 600 m/min, the feed rate of 0.12 and 0.15 mm/tooth, and axial depth of cut of 1.40 and 1.70 mm. 100 mL/h was set as MQL flow rate. Eight samples were performed on five axes milling machine according to a full factorial design. The tool wear was examined and measured progressively at every time interval using an optical microscope. From the analysis, MQL 100 mL/h at 500 m/min, 0.12 mm/tooth, and 1.40 mm was found to be better than dry machining. The adhesion wear mechanism was observed at both machining conditions. Near-dry machining with appropriate flow rate and machining parameters has the potential to contribute to long-term environmental friendly machining in line with the industrial revolution phase.

Application of Taguchi’s Method for Study of Machining Parameters on Surface Roughness of 7136 Aluminum Alloy in End Milling

2015 ◽  
Vol 809-810 ◽  
pp. 123-128 ◽  
Author(s):  
Alina Bianca Bonţiu Pop
Keyword(s):  
Surface Roughness ◽  
Aluminum Alloy ◽  
Process Parameters ◽  
End Milling ◽  
Signal To Noise Ratio ◽  
Cutting Speed ◽  
Cutting Parameters ◽  
Future Research ◽  
Depth Of Cut ◽  
Machining Parameters

Starting with the necessity to identify the optimum values of the cutting parameters which are affecting the surface quality, it is appropriate to use the design of experiment techniques to conduct the experiments. Previous researches [1] focused on the investigation of the effects of machining parameters on surface roughness. In this paper, the experiments were conducted based on the established Taguchi’s technique, L8 orthogonal array using Minitab-17 statistical software. Three machining parameters are chosen as process parameters: Cutting Speed, Feed per tooth and Depth of cut. The orthogonal matrix includes these three factors set for analysis, each with 2 levels associated. The level of influence that the process parameters exert on the surface roughness is analyzed by Taguchi method data analysis. In this case the signal to noise ratio was tacked into account. Also, the recommended configuration regarding the optimum values of these parameters was determined as well as the interactions between them, in order to obtain better surface roughness for 7136 aluminum alloy machining. The final results will be used as data for future research.

scholarly journals A Combined Experimental and Optimization Model to Improve the Machinability of Nimonic C-263 Superalloy

2020 ◽  
Author(s):  
Prashant Jadhav ◽  
Chinmaya Prasad Mohanty
Keyword(s):  
Process Parameters ◽  
Cutting Speed ◽  
Sem Analysis ◽  
Depth Of Cut ◽  
Process Conditions ◽  
Optimization Of Process Parameters ◽  
Excellent Mechanical Property ◽  
Single Response ◽  
Optimal Set ◽  
Super Alloy

Nickel based superalloys finds extensive usage in manufacturing of intricate part shapes in gas turbine, aircraft, submarine, and chemical industries owing their excellent mechanical property and heat resistant abilities. However, machining of such difficult-to-machine alloys up to the desired accuracy and preciseness is a complex task owing to a rapid tool wear and failure. In view of this, present work proposes an experimental investigation and optimization of process parameters of the cryogenic assisted turning process during machining of Nimonic C-263 super alloy with a multilayer CVD insert. Taguchi’s L-27 orthogonal array is used plan the experiments. Effect of input parameters viz. cutting speed (N), cutting feed (f), depth of cut (d) are studied on responses viz. surface roughness (SR), nose wear (NW) and cutting forces (F) under hybrid cryogenic (direct+indirect) machining environment. A scanning electron microscope (SEM) analysis is carried out to explore the post-machining outcomes on the performance measures. The multiple responses are converted in to single response and ranked according to Taguchi based gray relational grade (TGRG). Feed rate (f) is found to be the most influential parameter from the analysis of variance of GRG. The means of GRG for each level of process parameters are used to improve the optimal process parameters further. Finally, the confirmative experiment is performed with these optimal set of process parameters which showed an improvement of 9.34% in the value of GRG. The proposed work can be beneficial to choose ideal process conditions to enhance the performance of turning operation.

scholarly journals Optimization of CNC Turning Parameters in Machining EN19 using Face Centered Central Composite Design Based RSM

2020 ◽  
Vol 9 (2) ◽  
pp. 889-896
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Removal Rate ◽  
Cutting Speed ◽  
Vital Role ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Cnc Turning ◽  
Software Analysis ◽  
Central Composite

Manufacturing a defect free (quality) product is playing a vital role in today’s globally competitive, customer oriented era. Meeting the demand of the market by producing sufficient quantity is another challenge. Achieving greater production rates without compromising on quality, increases the complexity of the task. Adopting modern manufacturing methods like CNC turning are essential to meet the above requirements. EN19 is an important member in the family of alloy steels, which has a wide variety of applications in automobile and machine tool industries. Optimization of machining parameters is crucial in obtaining the required outputs such as quality and productivity. In this work, optimization of CNC turning parameters for machining EN19 alloy steel is performed. The number of experiments was designed using face centred central composite based response surface methodology with varied independent process parameters namely cutting speed, feed and depth of cut. After designing the experiments, the performance measures such as surface roughness of the test samples and Material Removal Rate (MRR) is calculated using the existing formulae. The influence of parameters on MRR and surface roughness are determined by analysis of variance (ANOVA) and for significance interactions of the process parameters are also considered. Using MINITAB 17 software analysis is performed. Further, regression analysis has been done and second order mathematical model is obtained. Using desirability approach, optimization is carried out.

Optimizing Feed Force in Turning Process Using Taguchi’s Parameter Design Approach

2014 ◽  
Vol 592-594 ◽  
pp. 668-672
Author(s):  
Praveen Kumar ◽  
Hari Singh
Keyword(s):  
Process Parameters ◽  
Feed Rate ◽  
Cutting Speed ◽  
Design Approach ◽  
Parameter Design ◽  
Depth Of Cut ◽  
Turning Process ◽  
Feed Force ◽  
Optimal Value ◽  
Optimal Setting

The objective of the paper is to obtain an optimal setting of turning process parameters (cutting speed, depth of cut and feed rate) resulting in an optimal value of the feed force when machining En19 steel with tungsten carbide cutting tool inserts. The effects of the selected turning process parameters on feed force and the subsequent optimal settings of the parameters have been accomplished using Taguchi’s parameter design approach. It was indicated by the results that the selected turning process parameters significantly affect the selected machining characteristic. The percent contributions of parameters as quantified in the S/N ANOVA envisage that the relative power of cutting speed (72.09 %) in controlling variation and mean feed force is significantly higher than that of the depth of cut (22.30 %) and feed rate (05.31 %). The predicted optimum feed force is 98.067 N. The results have been validated by the confirmation experiments.

Prediction the Influence of Machining Parameters for CNC Turning of Aluminum Alloy Using RSM and ANN

2020 ◽  
Vol 38 (6A) ◽  
pp. 887-895
Author(s):  
Hind H. Abdulridha ◽  
Aseel J. Haleel ◽  
Ahmed A. Al-duroobi
Keyword(s):  
Response Surface Methodology ◽  
Aluminum Alloy ◽  
Prediction Model ◽  
Response Surface ◽  
Feed Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Rsm Model ◽  
Good Agreement

The main objective of this paper is to develop a prediction model using Response Surface Methodology (RSM) and Artificial Neural Network (ANN) for the turning process of Aluminum alloy 6061 round rod. The turning experiments carried out based on the Central Composite Design (CCD) of Response Surface Methodology. The influence of three independent variables such as Cutting speed (150, 175 and 200 mm/ min), depth of cut (0.5, 1 and 1.5 mm) and feed rate (0.1, 0.2 and 0.3 mm/rev) on the Surface Roughness (Ra) were analyzed through analysis of variance (ANOVA). The response graphs from the Analysis of Variance (ANOVA) present that feed-rate has the strongest influence on Ra dependent on cutting speed and depth of cut. Surface response methodology developed between the machining parameters and response and confirmation experiments reveals that the good agreement with the regression models. The coefficient of determination value for RSM model is found to be high (R2 = 0.961). It indicates the goodness of fit for the model and high significance of the model. From the result, the maximum error between the experimental value and ANN model is less than the RSM model significantly. However, if the test patterns number will be increased then this error can be further minimized. The proposed RSM and ANN prediction model sufficiently predict Ra accurately. However, ANN prediction model is found to be better compared to RSM model. The artificial neutral network is applied to experimental results to find prediction results for two response parameters. The predicted results taken from ANN show a good agreement between experimental and predicted values with the mean squared error of training indices equal to (0.000) which produces flexibility to the manufacturing industries to select the best setting based on applications.

Relationship Between Measurement of Cutting Force and Sensor Location in Turning Process

2012 ◽  
Vol 59 (2) ◽  
Author(s):  
Jaharah A. Ghani ◽  
Poh Siang Jye ◽  
Che Hassan Che Haron ◽  
Muhammad Rizal ◽  
Mohd Zaki Nuawi
Keyword(s):  
Cutting Force ◽  
Strain Gauge ◽  
Cutting Speed ◽  
Strain Gauges ◽  
Depth Of Cut ◽  
Machining Parameters ◽  
Sensor Location ◽  
Turning Process ◽  
Feed Force ◽  
Cutting Point

Turning process is widely used in the production of components for automotive and aerospace applications. The machinability of a work material is commonly assessed in terms of cutting tool life, surface finish, and cutting force. These responses are dependent on machining parameters such as cutting speed, feed rate, and depth of cut. In this study, the relationships between cutting force, cutting speed, and sensor location in the turning process were investigated. Strain gauge was chosen as the sensor for the detection of cutting force signal during turning of hardened plain carbon steel JIS S45C. Two strain gauges were mounted on a tool holder at a defined location of I, II, or III at a distance of 37, 42, or 47 mm, respectively, from the cutting point. Only one set of machining experiments was conducted at spindle speed = 1000 rpm, feed = 0.25 mm/rev, and depth of cut = 0.80 mm. The turning process was stopped and the insert was discarded when average flank wear reached 0.30 mm. The main cutting force and the feed force for each cycle measured by the strain gauges at location I, II, and III were collected and analyzed. Results show that when cutting speed was increased, the main cutting force and the feed force were decreased accordingly. The change of was inversely proportional to the change of cutting speed, but the did not decrease continuously and behaved contrarily. A strain gauge placed at a distance of approximately 43 mm from the cutting point was found to be the best and most suitable for sensing accurate force signals.

scholarly journals The Possibility of Monitoring Forces during Turning Process of Shafts Made of AW-7020 Aluminium Alloy for Variable Treatment Conditions

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Aluminium Alloy ◽  
Cutting Speed ◽  
Radial Force ◽  
Cover Plate ◽  
Depth Of Cut ◽  
Turning Process ◽  
Treatment Conditions ◽  
Feed Force ◽  
Orthogonal Components ◽  
Cutting Insert

The article presents the research results referring to the analysis of the influence of cuttingparameters on value of cutting forces during turning pins of shaft. For the monitoring of forces during lathingprocess used Kistler dynamometer. The dynamometer is used for dynamic and quasistatic measurements of the3 orthogonal components of any forces acting on the cover plate (Fx - radial force, Fy - feed force andFz - cutting force). The turning process was carried out on a universal CU500MRD/1000 centre lathe. Theresearch was performed on a shaft made of 7020 aluminium alloy. Chemical composition of aluminium alloywas measured by Solaris-ccd plus optical spectrometer. The finishing turning process was carried out by cuttingtool with CCGT09T302-DL removable insert by Duracarb. During turning the following machining parameterswere used: cutting speed, feed and depth of cut. The goal of the paper was to define the influence of treatmentconditions on values of forces during turning process, and thus monitoring the wear of the cutting insert.

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